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Record W2164284837 · doi:10.1109/tcsi.2009.2024903

A 32/16-Gb/s Dual-Mode Pulsewidth Modulation Pre-Emphasis (PWM-PE) Transmitter With 30-dB Loss Compensation Using a High-Speed CML Design Methodology

2009· article· en· W2164284837 on OpenAlexaff
Anthony Chan Carusone, Hei Victor Cheng, F. A. S. Musa

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPulse-width modulationTransmitterDuty cycleModulation (music)Transmission (telecommunications)Computer sciencePulse-amplitude modulationElectronic engineeringElectrical engineeringPulse (music)PhysicsChannel (broadcasting)TelecommunicationsEngineeringVoltageAcoustics

Abstract

fetched live from OpenAlex

Pulse-width modulation pre-emphasis (PWM-PE) is a relatively new technique for compensating severe losses in wireline channels by varying the duty cycle of the transmitted pulse. The technique has been demonstrated upto 5 Gb/s and requires high-speed digital logic to accomodate narrow pulses in the transmitted bit stream. This work targets data rates beyond 10 Gb/s and extends PWM-PE to 4-PAM signals in addition to binary mode transmission. The target speed is achieved by designing the transmitter using current mode logic (CML) blocks that combine relatively large logic swings and incomplete switching of the tail current. Implemented in a 0.13-¿m CMOS process to accommodate the wide output swing of 1.2 Vpp per side, the transmitter compensates upto 30 dB loss at one-half the symbol rate and operates up to 16 Gsymbols/s.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.269
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2009
Admission routes1
Has abstractyes

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